The Exam P
5-Week Bootcamp

Register Today!






Join a 5-week intensive program offering weekly live and interactive lectures of key exam syllabus topics and related problem solving review plus the opportunity for each student to receive individual tutoring assistance and support from the instructor throughout the program.

Charles Major has accumulated over 40 years of experience in leading students to academic and actuarial exam success.  Professor Major leads classes at both New York University and University of North Florida for students preparing for their actuarial exams, specializing in Exams P, FM, and IFM.  Professor Major holds a BS in Math and Statistics from University of New Hampshire, MS in Math, Statistics, and Operations Research for Finance from New York University, and is working towards a PhD in Math and Science from University of New Hampshire.

The Exam P 5-Week Bootcamp provides the following:

  1. Weekly 2 hour live online class lecture which will integrate concept building and technique practicing with problem solving. Live classes are interactive in nature and students are encouraged to ask questions of lead instructor
  2. Open Forum immediately following each weekly lecture in which students can ask instructor questions related to all topics/exam problem solving
  3. Weekly problem sets to reinforce material reviewed during live lectures
  4. Online office hours support available each week
  5. Private mini-sessions available with instructor to discuss and review specific problem areas
  6. Q & A email correspondence in which students can always email program instructor questions with quick reply back
  7. Students can elect to join The Exam P Discussion Group consisting only of program members to communicate with each other
  8. All weekly lectures recorded and distributed to program members

Schedule

Live Classes & Subjects

Lecture 1: 4/18
12:15 PM - 2:15 PM EST
1. Conditional Probability
2. Bayes Theorem
3. Combinatorics
4. Discrete Probability Distributions, Mean, Expectation, MGF
a. Binomial
b. Poisson
c. Geometric
d. Hypergeometric
e. Negative Binomial
Lecture 2: 4/25
10:00 AM - 12:00 PM EST
1. Continuous Probability Distributions, Mean, Expectation, MGF
a. Normal Distribution
b. Inverse Normal Distribution
c. Uniform Distribution
d. Exponential Distribution
e. Beta Distribution
f. Gamma Distribution
Lecture 3: 4/28
7:00 PM - 9:00 PM EST
1. Expectation, Variance Convolution, Univariate, Multivariate
2. Conditional Expectation
3. General Law of Expectation
4. Conditional Variance
5. Covariance
6. Application of Multivariate Distributions
Lecture 4: 5/2
10:00 AM- 12:00 PM EST
1. Risk Management Applications
a. Loss Distribution and Insurance
b. Partial Insurance Coverage
c. Policy Limits Applications
d. Proportional Insurance
e. Individual Risk Modeling
f. Aggregate Claims Processing
g. Loss Distributions by Conditioning
Lecture 5: 5/9
10:00 AM - 12:00 PM EST
1. Set Theory and Venn Diagrams
2. Normal Approximation for Discrete Distributions

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